Identifying hybridization and admixture using SNPs: Application of the DArTseq platforminphylogeographic research on vertebrates

Jane Melville, Margaret L. Haines, Katja Boysen, Luke Hodkinson, Andrzej Kilian, Katie L. Smith Date, Dominique A. Potvin, Kirsten M. Parris

Research output: Contribution to journalArticlepeer-review

86 Citations (Scopus)
184 Downloads (Pure)

Abstract

Next-generation sequencing (NGS) approaches are increasingly being used to generate multi-locus data for phylogeographic and evolutionary genetics research. We detail the applicability of a restriction enzyme-mediated genome complexity reduction approach with subsequent NGS (DArTseq) in vertebrate study systems at different evolutionary and geographical scales. We present two case studies using SNP data from the DArTseq molecular marker platform. First, we used DArTseq in a large phylogeographic study of the agamid lizard Ctenophorus caudicinctus, including 91 individuals and spanning the geographical range of this species across arid Australia. A low-density DArTseq assay resulted in 28 960 SNPs, with low density referring to a comparably reduced set of identified and sequenced markers as a cost-effective approach. Second, we applied this approach to an evolutionary genetics study of a classic frog hybrid zone (Litoria ewingii–Litoria paraewingi) across 93 individuals, which resulted in 48 117 and 67 060 SNPs for a low- and high-density assay, respectively. We provide a docker-based workflow to facilitate data preparation and analysis, then analyse SNP data using multiple methods including Bayesian model-based clustering and conditional likelihood approaches. Based on comparison of results from the DArTseq platform and traditional molecular approaches, we conclude that DArTseq can be used successfully in vertebrates and will be of particular interest to researchers working at the interface between population genetics and phylogenetics, exploring species boundaries, gene exchange and hybridization.

Original languageEnglish
Article number161061
Pages (from-to)1-14
Number of pages14
JournalRoyal Society Open Science
Volume4
Issue number7
DOIs
Publication statusPublished - 19 Jul 2017

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